[HTML][HTML] A comprehensive survey of image augmentation techniques for deep learning
Although deep learning has achieved satisfactory performance in computer vision, a large
volume of images is required. However, collecting images is often expensive and …
volume of images is required. However, collecting images is often expensive and …
Efficient deep learning: A survey on making deep learning models smaller, faster, and better
G Menghani - ACM Computing Surveys, 2023 - dl.acm.org
Deep learning has revolutionized the fields of computer vision, natural language
understanding, speech recognition, information retrieval, and more. However, with the …
understanding, speech recognition, information retrieval, and more. However, with the …
Machine learning algorithms in civil structural health monitoring: A systematic review
M Flah, I Nunez, W Ben Chaabene… - Archives of computational …, 2021 - Springer
Abstract Applications of Machine Learning (ML) algorithms in Structural Health Monitoring
(SHM) have become of great interest in recent years owing to their superior ability to detect …
(SHM) have become of great interest in recent years owing to their superior ability to detect …
Parallel learning: Overview and perspective for computational learning across Syn2Real and Sim2Real
Q Miao, Y Lv, M Huang, X Wang… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
The virtual-to-real paradigm, ie, training models on virtual data and then applying them to
solve real-world problems, has attracted more and more attention from various domains by …
solve real-world problems, has attracted more and more attention from various domains by …
On translation invariance in cnns: Convolutional layers can exploit absolute spatial location
In this paper we challenge the common assumption that convolutional layers in modern
CNNs are translation invariant. We show that CNNs can and will exploit the absolute spatial …
CNNs are translation invariant. We show that CNNs can and will exploit the absolute spatial …
A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning
Limited condition monitoring data are recorded with label information in practice, which
make the fault identification task more challenging. A semi-supervised learning (SSL) …
make the fault identification task more challenging. A semi-supervised learning (SSL) …
An efficient multi-scale CNN model with intrinsic feature integration for motor imagery EEG subject classification in brain-machine interfaces
AM Roy - Biomedical Signal Processing and Control, 2022 - Elsevier
Objective Electroencephalogram (EEG) based motor imagery (MI) classification is an
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …
Regularization for deep learning: A taxonomy
Regularization is one of the crucial ingredients of deep learning, yet the term regularization
has various definitions, and regularization methods are often studied separately from each …
has various definitions, and regularization methods are often studied separately from each …
Knowledge distillation improves graph structure augmentation for graph neural networks
Graph (structure) augmentation aims to perturb the graph structure through heuristic or
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
probabilistic rules, enabling the nodes to capture richer contextual information and thus …
Failures of Photovoltaic modules and their Detection: A Review
Photovoltaic (PV) has emerged as a promising and phenomenal renewable energy
technology in the recent past and the PV market has developed at an exponential rate …
technology in the recent past and the PV market has developed at an exponential rate …